040331 KU Empirical Methods in Decision Sciences (MA) (2020S)
Prüfungsimmanente Lehrveranstaltung
Labels
service email address: opim.bda@univie.ac.at
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 10.02.2020 09:00 bis Mi 19.02.2020 12:00
- Anmeldung von Di 25.02.2020 09:00 bis Mi 26.02.2020 12:00
- Abmeldung bis Do 30.04.2020 23:59
Details
max. 33 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
-
Mittwoch
04.03.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
11.03.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
18.03.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
25.03.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
01.04.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
22.04.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
29.04.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
06.05.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
13.05.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
20.05.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
27.05.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
03.06.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
10.06.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
17.06.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock -
Mittwoch
24.06.
15:00 - 16:30
PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
In this course students are introduced to decision science relevant empirical methods. The major focus point of the course is the design and implementation of computerized interactive and static experiments. Students are introduced to the theoretical knowledge about various experimental designs, practical implementation of the designed experiment using Python language based platform and analysis of the results using Python & R based tools. Principal interest in computer programming can be helpful for this course. The course is taught in English.The programming languages and tools used in the course are platform independent, nevertheless it is highly recommended to bring a laptop for students’ own convenience.
Art der Leistungskontrolle und erlaubte Hilfsmittel
Written exam concerning theoretical design knowledge
oTree assignments
Data analysis assignments
oTree assignments
Data analysis assignments
Mindestanforderungen und Beurteilungsmaßstab
Participation in the first class is mandatory!
First class will be held in SR 16.
Students need a laptop for oTree and data analysis assignments.
All partial achievements (exam & assignments) must be positive in order to have a positive grade from the course.
0-50 points => 5
51-63 points => 4
64-75 points => 3
76-87 points => 2
88-100 points => 1
First class will be held in SR 16.
Students need a laptop for oTree and data analysis assignments.
All partial achievements (exam & assignments) must be positive in order to have a positive grade from the course.
0-50 points => 5
51-63 points => 4
64-75 points => 3
76-87 points => 2
88-100 points => 1
Prüfungsstoff
Course content
During the closure of university buildings, this course will be held online. Course materials and important informations regarding the course will be made available on Moodle. Please check regularly for new additions.
During the closure of university buildings, this course will be held online. Course materials and important informations regarding the course will be made available on Moodle. Please check regularly for new additions.
Literatur
Douglas, C. M. (2019). Design analysis of Experiments. John Wiley & Sons
Donohue, K., Katok, E., & Leider, S. (Eds.). (2018). The handbook of behavioral operations. John Wiley & Sons.
Guttag, J. V. (2013). Introduction to computation and programming using Python. Mit Press.
For oTree: https://otree.readthedocs.io/en/latest/
For Python: https://www.python.org
For JupyterLab: https://jupyterlab.readthedocs.io/en/stable/
For R: https://www.r-project.org
Donohue, K., Katok, E., & Leider, S. (Eds.). (2018). The handbook of behavioral operations. John Wiley & Sons.
Guttag, J. V. (2013). Introduction to computation and programming using Python. Mit Press.
For oTree: https://otree.readthedocs.io/en/latest/
For Python: https://www.python.org
For JupyterLab: https://jupyterlab.readthedocs.io/en/stable/
For R: https://www.r-project.org
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 07.09.2020 15:19